The PV SoilSayer utilizes industry standard PV performance modeling software, advanced machine learning algorithms combined with historical weather as well as long-term weather forecasts and PV system soiling estimations to calculate estimated losses, optimal cleaning schedules and net financial returns.
The PV SoilSayer is designed to give users full control over modeling the cost trade-offs associated with soiling. Users can choose from a number of different options for calculating soiling losses or uploading measured data. In addition, there several options for running different cleaning scenarios to better understand the cost trade-offs for a given clean cycle.
Detailed reports provide users with estimates of cost trade-offs associated with a specified clean cycle.
Users can compare soiling losses and associated costs, as well as the value of energy gain for a given clean cycle, in order to make informed decisions about the frequency and timing for cleaning the PV system.
Interactive charts provide users with valuable insights into daily, monthly, and annual precipitation patterns, soiling trends and associated losses.